Weighing the impact (factor) of publishing in veterinary journals

Data-Mining Methodology to Improve the Scientific Production Quality in Turkey Meat and Carcass Characterization Studies

The present research aims to describe how turkey meat and carcass quality traits define the interest of the scientific community through the quality standards of journals in which studies are published. To this end, an analysis of 92 research documents addressing the study of turkey carcass and meat quality over the last 57 years was performed. Meat and carcass quality attributes were dependent variables and included traits related to carcass dressing, muscle fiber, pH, colorimetry, water-holding capacity, texture, and chemical composition. The independent variables comprised publication quality traits, including journal indexation, database, journal impact factor (JIF), quartile, publication area, and JIF percentage. For each dependent variable, a data-mining chi-squared automatic interaction detection (CHAID) decision tree was developed. Carcass or piece yield was the only variable that did not show an impact on the publication quality. Moreover, color and pH measurements taken at 72 h postmortem showed a negative impact on publication interest. On the other hand, variables including water-retaining attributes, colorimetry, pH, chemical composition, and shear force traits stood out among the quality-enhancing variables due to their low inclusion in papers, while high standards improved power.

Comprehensive analysis of retracted journal articles in the field of veterinary medicine and animal health

Background

Retractions are a key proxy for recognizing errors in research and publication and for reconciling misconduct in the scientific literature. The underlying factors associated with retractions can provide insight and guide policy for journal editors and authors within a discipline. The goal of this study was to systematically review and analyze retracted articles in veterinary medicine and animal health. A database search for retractions of articles with a veterinary/animal health topic, in a veterinary journal, or by veterinary institution-affiliated authors was conducted from first available records through February 2019 in MEDLINE/PubMed, Web of Science, Scopus, Retraction Watch, and Google Scholar. Annual frequency of retractions, journal and article characteristics, author affiliation and country, reasons for retraction, and retraction outcomes were recorded.

Results

Two-hundred-forty-two articles retracted between 1993 and 2019 were included in the study. Over this period, the estimated rate of retraction increased from 0.03/1000 to 1.07/1000 veterinary articles. Median time from publication to retraction was 478 days (range 0-3653 days). Retracted articles were published in 30 (12.3%) veterinary journals and 132 (81.5%) nonveterinary journals. Veterinary journals had disproportionately more retractions than nonveterinary journals (P = .0155). Authors/groups with ≥2 retractions accounted for 37.2% of retractions. Authors from Iran and China published 19.4 and 18.2% of retracted articles respectively. Authors were affiliated with a faculty of veterinary medicine in 59.1% of retracted articles. Of 242 retractions, 204 (84.3%) were research articles, of which 6.4% were veterinary clinical research. Publication misconduct (plagiarism, duplicate publication, compromised peer review) accounted for 75.6% of retractions, compared with errors (20.6%) and research misconduct (18.2%). Journals published by societies/institutions were less likely than those from commercial publishers to indicate a reason for retraction. Thirty-one percent of HTML articles and 14% of PDFs were available online but not marked as retracted.

Conclusions

The rate of retraction in the field of veterinary and animal health has increased by ~ 10-fold per 1000 articles since 1993, resulting primarily from increased publication misconduct, often by repeat offenders. Veterinary journals and society/institutional journals could benefit from improvement in the quality of retraction notices.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-022-03167-x.

Questioning the Impact of the Impact Factor. A Brief Review and Future Directions

Purpose: To provide a brief review of literature on the journal impact factors (JIF) and the newer research metrics being proposed or implemented.Methods: The authors performed a PubMed search of articles published in the English language on the journal impact factors. Data captured include historical perspectives, evolution, calculation, criticisms of JIF and their rebuttals, and organized efforts to address JIF issues, alternate research metrics, and future directions. Specific emphasis was laid on evaluating the criticisms, current lacunae, and the changing practice patterns.Results: One of the measures to assess the research impact of an article is the number of citations it receives. Hence, citation-based metrics are commonly used for such purposes. While editors and well-known scholars refrain from attributing article success to the journal's prominence, the same is not true for most authors. JIF is still one of the top factors when deciding on an article submission. JIF is today an acceptable objective and quantifiable measure of knowledge dissemination. However, JIF should not be used as a surrogate measure to assess an individual researcher or an individual article. The reverence to JIF in this regard needs to be questioned. While alternate metrics or altmetrics have their advantages and limitations, they nevertheless augur well an era where scientometrics are complementary to one another without undue reliance on a sole parameter.Conclusion: While there is no need to demonize the JIF, its role in the scholarly assessment should be scaled down. The over-reliance and undue hype surrounding it should be discouraged at multiple scientific levels.

Systematic analysis of the scientific literature on population surveillance

Introduction

Population surveillance provides data on the health status of the population through continuous scrutiny of different indicators. Identifying risk factors is essential for the quickly detecting and controlling of epidemic outbreaks and reducing the incidence of cross-infections and non-communicable diseases. The objective of the present study is to analyze research on population surveillance, identifying the main topics of interest for investigators in the area.

Methodology

We included documents indexed in the Web of Science Core Collection in the period from 2000 to 2019 and assigned with the generic Medical Subject Heading (MeSH) “population surveillance” or its related terms (“public health surveillance,” “sentinel surveillance” or “biosurveillance”). A co-occurrence analysis was undertaken to identify the document clusters comprising the main research topics. Scientific production, collaboration, and citation patterns in each of the clusters were characterized bibliometrically. We also analyzed research on coronaviruses, relating the results obtained to the management of the COVID-19 pandemic.

Results

We included 39,184 documents, which reflected a steady growth in scientific output driven by papers on “Public, Environmental & Occupational Health” (21.62% of the documents) and “Infectious Diseases” (10.49%). Research activity was concentrated in North America (36.41%) and Europe (32.09%). The USA led research in the area (40.14% of documents). Ten topic clusters were identified, including “Disease Outbreaks,” which is closely related to two other clusters (“Genetics” and “Influenza”). Other clusters of note were “Cross Infections” as well as one that brought together general public health concepts and topics related to non-communicable diseases (cardiovascular and coronary diseases, mental diseases, diabetes, wound and injuries, stroke, and asthma). The rest of the clusters addressed “Neoplasms,” “HIV,” “Pregnancy,” “Substance Abuse/Obesity,” and “Tuberculosis.” Although research on coronavirus has focused on population surveillance only occasionally, some papers have analyzed and collated guidelines whose relevance to the dissemination and management of the COVID-19 pandemic has become obvious. Topics include tracing the spread of the virus, limiting mass gatherings that would facilitate its propagation, and the imposition of quarantines. There were important differences in the scientific production and citation of different clusters: the documents on mental illnesses, stroke, substance abuse/obesity, and cross-infections had much higher citations than the clusters on disease outbreaks, tuberculosis, and especially coronavirus, where these values are substantially lower.

Conclusions

The role of population surveillance should be strengthened, promoting research and the development of public health surveillance systems in countries whose contribution to the area is limited.

Incomplete reporting of experimental studies and items associated with risk of bias in veterinary research

In in vivo research, the reporting of core items of study design is persistently poor, limiting assessment of study quality and study reproducibility. This observational cohort study evaluated reporting levels in the veterinary literature across a range of species, journals and research fields. Four items (randomisation, sample size estimation, blinding and data exclusion) were assessed as well as availability of study data in publicly accessible repositories. From five general and five subject-specific journals, 120 consecutively published papers (12 per journal) describing in vivo experimental studies were selected. Item reporting was scored using a published scale (items ranked as fully, partially or not reported) according to completeness of reporting. Papers in subject-specific journals had higher median reporting levels (50.0 per cent vs 33.3 per cent, P=0.007). In subject-specific journals, randomisation (75.0 per cent vs 41.7 per cent, P=0.0002) and sample size estimation (35.0 per cent vs 16.7 per cent, P=0.025) reporting was approximately double that of general journals. Blinding (general 48.3 per cent, subject-specific 50.0 per cent, P=0.86) and data exclusion (general 53.3 per cent, subject-specific 63.3 per cent, P=0.27) were similarly reported. A single paper made study data readily accessible. Incomplete reporting remains prevalent in the veterinary literature irrespective of journal type, research subject or species. This impedes evaluation of study quality and reproducibility, raising concerns regarding wasted financial and animal resources.

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models

OBJECTIVES

Effective researcher assessment is key to decisions about funding allocations, promotion and tenure. We aimed to identify what is known about methods for assessing researcher achievements, leading to a new composite assessment model.

DESIGN

We systematically reviewed the literature via the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols framework.

DATA SOURCES

All Web of Science databases (including Core Collection, MEDLINE and BIOSIS Citation Index) to the end of 2017. ELIGIBILITY CRITERIA: (1) English language, (2) published in the last 10 years (2007-2017), (3) full text was available and (4) the article discussed an approach to the assessment of an individual researcher's achievements.

DATA EXTRACTION AND SYNTHESIS

Articles were allocated among four pairs of reviewers for screening, with each pair randomly assigned 5% of their allocation to review concurrently against inclusion criteria. Inter-rater reliability was assessed using Cohen's Kappa (ĸ). The ĸ statistic showed agreement ranging from moderate to almost perfect (0.4848-0.9039). Following screening, selected articles underwent full-text review and bias was assessed.

RESULTS

Four hundred and seventy-eight articles were included in the final review. Established approaches developed prior to our inclusion period (eg, citations and outputs, h-index and journal impact factor) remained dominant in the literature and in practice. New bibliometric methods and models emerged in the last 10 years including: measures based on PageRank algorithms or 'altmetric' data, methods to apply peer judgement and techniques to assign values to publication quantity and quality. Each assessment method tended to prioritise certain aspects of achievement over others.

CONCLUSIONS

All metrics and models focus on an element or elements at the expense of others. A new composite design, the Comprehensive Researcher Achievement Model (CRAM), is presented, which supersedes past anachronistic models. The CRAM is modifiable to a range of applications.